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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimizing equity in energy policy interventions: A quantitative decision-support framework for energy justice

This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Kinetics-Informed Neural Networks

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by differential algebraic equations (DAEs) that describe microkinetic models (MKMs). We present an algebraic framework for the mathematical description and classification of reaction networks, types of elementary reaction, and chemical species. Under this framework, we demonstrate that the simultaneous training of neural nets and kinetic model parameters in a regularized multi-objective optimization setting leads to the solution of the inverse problem through the estimation of kinetic parameters from synthetic experimental data. We analyze a set of scenarios to establish the extent to which kinetic parameters can be retrieved from transient kinetic data, and assess the robustness of the methodology with respect to statistical noise. Furthermore, this approach to inverse kinetic ODEs can assist in the elucidation of reaction mechanisms based on transient data.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials

Purpose: To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system. Methods and Materials: We analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volume histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V{sub 10} (percentage volume of PBM receiving at least 10 Gy dose) and V{sub 20} (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V{sub 40} (absolute volume of bowel receiving at least 40 Gy dose) and V{sub 45} (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning “routine”). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBP{sub FINAL}), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBP{sub FINAL} plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets. Results: KBP{sub FINAL} plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBP{sub FINAL} versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBP{sub FINAL} plans, indicating lowered probability of hematologic toxicity. Conclusions: This work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Evapotranspiration across plant types and geomorphological units in polygonal Arctic tundra

Coastal tundra ecosystems are relatively flat, and yet display large spatial variability in ecosystem traits. The microtopographical differences in polygonal geomorphology produce heterogeneity in permafrost depth, soil temperature, soil moisture, soil geochemistry, and plant distribution. Few measurements have been made, however, of how water fluxes vary across polygonal tundra plant types, limiting our ability to understand and model these ecosystems. In this study, our objective was to investigate how plant distribution and geomorphological location affect actual evapotranspiration (ET). These effects are especially critical in light of the rapid change polygonal tundra systems are experiencing with Arctic warming. At a field site near Barrow, Alaska, USA, we investigated the relationships between ET and plant cover in 2014 and 2015. ET was measured at a range of spatial and temporal scales using: (1) An eddy covariance flux tower for continuous landscape-scale monitoring; (2) An automated clear surface chamber over dry vegetation in a fixed location for continuous plot-scale monitoring; and (3) Manual measurements with a clear portable chamber in approximately 60 locations across the landscape. We found that variation in environmental conditions and plant community composition, driven by microtopographical features, has significant influence on ET. Among plant types, ET from moss-covered and inundated areas was more than twice that from other plant types. ET from troughs and low polygonal centers was significantly higher than from high polygonal centers. ET varied seasonally, with peak fluxes of 0.14 mm h -1 in July. Despite 24 hours of daylight in summer, diurnal fluctuations in incoming solar radiation and plant processes produced a diurnal cycle in ET. Finally, combining the patterns we observed with projections for the impact of permafrost degradation on polygonal structure suggests that microtopographic changes associated with permafrost thaw have the potential to alter tundra ecosystem ET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improving the prediction of daily reservoir releases over the CONUS using conditioned LSTM

Reservoirs play a vital role in regulating streamflow timing and variability for hydroelectricity, flood control, water supply, irrigation, and recreation. Despite their importance, many reservoirs lack comprehensive operational guidelines, making their management complex due to conflicting operational objectives. Hence traditional policy-based reservoir models often fail to capture real-world conditions accurately and they depend on perfect streamflow predictions, which are not always available. In contrast, data-driven models like Long Short-Term Memory (LSTM) networks offer a robust alternative. This study introduces an approach that integrates reservoir characteristics—such as main use, climate, and maximum capacity—into the LSTM model to enhance reservoir release predictions. Using data from nearly 200 reservoirs in the contiguous United States (CONUS), our conditioned LSTM model (LSTM_cond) was compared with both the vanila LSTM and a traditional policy-based approach. Furthermore, our results show that while both LSTM_cond and LSTM perfoms better than the policy-based approach, LSTM_cond consistently outperforms LSTM for hydroelectric, water supply, irrigation, and recreation reservoirs. The KGE median values for LSTM_cond for out-sample reservoirs are 0.764, 0.565, 0.821, and 0.779, respectively, for the aforementioned reservoir types, which are consistently higher that the corresponding KGE values of 0.737, 0.413, 0.775, and 0.713 of LSTM, demonstrating its advantages in improving generalizability.

CONUS↗
DOE OSTI2022

Mesh objective stochastic simulations of quasibrittle fracture

Continuum finite element (FE) modeling of damage and failure of quasibrittle structures suffers from the spurious mesh sensitivity due to strain localization. Here this issue has been addressed for deterministic analysis through the development of localization limiters. Here this study proposes a mechanism-based model to mitigate the mesh sensitivity in stochastic FE simulations of quasibrittle fracture. The interest is placed on the analysis of large-size structures, where the mesh size is conveniently chosen to be larger than the width of the fracture process zone as well as the correlation length of the random fields of constitutive properties. The present model is formulated within the framework of continuum damage mechanics. Two localization parameters are introduced to describe the evolution of the damage pattern of each finite element. These parameters are used to guide the energy regularization of the constitutive law, as well as to formulate the mesh-dependent probability distributions of constitutive properties. Depending on the prevailing damage pattern, different energy regularization schemes and mesh dependence of the probability distribution functions are used in the constitutive law. The model is applied to simulate the stochastic failure behavior of quasibrittle structures of different geometries featuring different failure processes including damage initiation, localization, and propagation. It is shown that using fixed probability distribution functions of constitutive properties could lead to strong mesh dependence of the prediction of the mean and variance of the structural load capacity. The probability distribution functions of constitutive properties must be linked to the damage pattern, which may evolve during the failure process. Such a mechanism-based modeling of the probability distributions of constitutive properties is essential for mitigating the spurious mesh sensitivity in stochastic FE analysis of quasibrittle fracture.

42 ENGINEERING↗
DOE OSTI2019

Brush-Modified Materials: Control of Molecular Architecture, Assembly Behavior, Properties and Applications

Recent progress in surface-initiated polymerization enables the deliberate polymer modification of nanoscopic surfaces with high levels of precision. This has given rise to the development of brush particle-based materials (sometimes referred to as ‘hairy nanoparticles’) that are formed by tethering of polymer chains to the surface of nanoparticle-like objects. Brush particles have attracted interest as model systems to understand the effect of surface modification on the structure and interactions in polymer modified colloidal systems (which play a role across fields as diverse as functional coatings, cosmetics, foods or pharmaceuticals) but also as building blocks for the assembly of ‘one-component hybrid materials’ that exhibit unprecedented property combinations, not realizable in classical composite materials. This review presents a summary and analysis of the developments in the field of ‘particle brush materials’. The evolution of synthetic methodologies from the original pioneering work to emerging trends and opportunities in the field of brush synthesis is presented first. Subsequently, the effect of brush architecture on the structure, interaction and assembly of brush particles both with and without a matrix is discussed. Lastly, recent advances in the development of functional hybrid materials with applications in energy, catalysis, sensing and other areas is presented.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observing flow of He II with unsupervised machine learning

Abstract Time dependent observations of point-to-point correlations of the velocity vector field (structure functions) are necessary to model and understand fluid flow around complex objects. Using thermal gradients, we observed fluid flow by recording fluorescence of $${\text{He}}_{2}^{*}$$ He 2 ∗ excimers produced by neutron capture throughout a ~ cm 3 volume. Because the photon emitted by an excited excimer is unlikely to be recorded by the camera, the techniques of particle tracking (PTV) and particle imaging (PIV) velocimetry cannot be applied to extract information from the fluorescence of individual excimers. Therefore, we applied an unsupervised machine learning algorithm to identify light from ensembles of excimers (clusters) and then tracked the centroids of the clusters using a particle displacement determination algorithm developed for PTV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Tracing ultrafast dynamics of strong fields at plasma-vacuum interfaces with longitudinal proton probing

If regions of localized strong fields at plasma-vacuum interfaces are probed longitudinally with laser accelerated proton beams their velocity distribution changes sensitively and very fast. Its measured variations provide indirectly a higher temporal resolution as deduced from deflection geometries which rely on the explicit temporal resolution of the proton beam at the position of the object to probe. With help of reasonable models and comparative measurements changes of proton velocity can trace the field dynamics even at femtosecond time scale. In longitudinal probing, the very low longitudinal emittance together with a broad band kinetic energy distribution of laser accelerated protons is the essential prerequisite of the method. With a combination of energy and one-dimensional spatial resolution, we resolve fast field changes down to 100 fs. The used pump probe setup extends previous schemes and allows discriminating simultaneously between electric and magnetic fields in their temporal evolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Demand forecasting for automotive sector in Malaysia by system dynamics approach

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Impact of cross-linking of polymers on transport of salt and water in polyelectrolyte membranes: A mesoscopic simulation study

Our recent atomistic simulation studies demonstrated that the transport properties of salt ions and water in non-crosslinked polymer electrolyte membrane exhibit an intriguing dependence on salt concentration that is opposite to that seen in electrolyte solutions. Here in this paper, we extend our study to probe the influence of the degree of cross-linking of the polymer on the transport properties of salt and water in polymer electrolyte membranes. Towards this objective, we use a coarse-grained model embedded within dissipative particle dynamics (DPD) mesoscale simulations, which allows us to access time scales necessary for studying crosslinked polymer systems. Our DPD simulations on non-crosslinked membranes reproduce results that are in qualitative agreement with our atomistic simulations. For the case of crosslinked membranes, our results demonstrate that the diffusion of salt ions and water is reduced significantly relative to crosslinked systems. However, the trends exhibited by the salt concentration dependence of diffusivities and the coordination of the cations with anions and with the polymer backbone remain qualitatively similar to those observed in non-crosslinked membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The ASHRAE Great Energy Predictor III competition: Overview and results

In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning competition on the Kaggle platform. This launch marked the third energy prediction competition from ASHRAE and the first since the mid-1990s. In this updated version, the competitors were provided with over 20 million points of training data from 2,380 energy meters collected for 1,448 buildings from 16 sources. This competition’s overall objective was to find the most accurate modeling solutions for the prediction of over 41 million private and public test data points. Furthermore, the competition had 4,370 participants, split across 3,614 teams from 94 countries who submitted 39,403 predictions. In addition to the top five winning workflows, the competitors publicly shared 415 reproducible online machine learning workflow examples (notebooks), including over 40 additional, full solutions. This paper gives a high-level overview of the competition preparation and dataset, competitors and their discussions, machine learning workflows and models generated, winners and their submissions, discussion of lessons learned, and competition outputs and next steps. The most popular and accurate machine learning workflows used large ensembles of mostly gradient boosting tree models, such as LightGBM. Similar to the first predictor competition, preprocessing of the data sets emerged as a key differentiator.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

THE BURST CLUSTER: DARK MATTER IN A CLUSTER MERGER ASSOCIATED WITH THE SHORT GAMMA-RAY BURST, GRB 050509B

We have identified a merging galaxy cluster with evidence of two distinct subclusters. The X-ray and optical data suggest that the subclusters are presently moving away from each other after closest approach. This cluster merger was discovered from observations of the first well-localized short-duration gamma-ray burst (GRB), GRB 050509B. The Swift/Burst Alert Telescope error position of the source is coincident with a cluster of galaxies ZwCl 1234.0+02916, while the subsequent Swift/X-Ray Telescope localization of the X-ray afterglow found the GRB coincident with 2MASX J12361286+2858580, a giant red elliptical galaxy in the cluster. Deep multi-epoch optical images were obtained in this field to constrain the evolution of the GRB afterglow, including a total of 27,480 s exposure in the F814W band with Hubble Space Telescope Advanced Camera for Surveys, among the deepest imaging ever obtained toward a known galaxy cluster in a single passband. We perform a weak gravitational lensing analysis based on these data, including mapping of the total mass distribution of the merger system with high spatial resolution. When combined with Chandra X-ray Observatory Advanced CCD Imaging Spectrometer and Swift/XRT observations, we are able to investigate the dynamical state of the merger to better understand the nature of the dark matter component. Our weak gravitational lensing measurements reveal a separation of the X-ray centroid of the western subcluster from the center of the mass and galaxy light distributions, which is somewhat similar to that of the famous 'Bullet cluster', and we conclude that this 'Burst cluster' adds another candidate to the previously known merger systems for determining the nature of dark matter, as well as for studying the environment of a short GRB. Finally, we discuss potential connections between the cluster dynamical state and/or matter composition, and compact object mergers, which is currently the leading model for the origin of short GRBs. We also present our results from a weak-lensing survey based on archival Very Large Telescope images in the areas of five other short GRBs, which do not provide any firm detections of mass concentrations representative of rich clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A theoretical study on the interstellar synthesis of H{sub 2}NCS{sup +} and HNCSH{sup +} cations

HNCS and NCSH molecules, recently discovered in the interstellar medium, are likely formed via the dissociative recombination of H{sub 2}NCS{sup +} or HNCSH{sup +} isomeric ions. Interstellar synthesis of the latter is discussed on theoretical grounds. The analysis of relevant potential energy surfaces suggests a key role for chemical processes in which CSH{sup +} or HCS{sup +} cations (most likely formed in CS+H{sub 3}{sup +} collisions) react with NH{sub 2} or NH{sub 3}. The astrochemical kinetic database (kida.uva.2011), appended with 7 sulfur-bearing molecules and 48 corresponding reactions, has been applied to model the evolution of HNCS, NCSH, and their cationic precursors in a quiescent molecular cloud. Based on the model and on spectroscopic predictions, for an object like TMC-1, we expect the total intensity of H{sub 2}NCS{sup +} microwave lines to be comparable to that observed for HSCN. Theoretically derived molecular parameters, of interest for radio spectroscopy, are given for the most stable cations sharing the H{sub 2}NCS{sup +} stoichiometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Highest Energy HAWC Sources are Likely Leptonic and Powered by Pulsars

The HAWC Collaboration has observed gamma rays at energies above 56 TeV from a collection of nine sources. It has been suggested that this emission could be hadronic in nature, requiring that these systems accelerate cosmic-ray protons or nuclei up to PeV-scale energies. In this paper, we instead show that the spectra of these objects favor a leptonic (inverse Compton) origin for their emission. More specifically, the gamma-ray emission from these objects can be straightforwardly accommodated within a model in which $\sim \mathcal{O}(10\%)$ of the host pulsar's spindown power is transferred into the acceleration of electrons and positrons with a power-law spectrum that extends to several hundred TeV or higher. The spectral break that is observed among these sources is naturally explained within the context of this simple model, and occurs at the energy where the timescale for energy losses matches the age of the pulsar. In contrast, this spectral feature cannot be straightforwardly accommodated in hadronic scenarios. Furthermore, hadronic models predict that these sources should produce more emission at GeV-scale energies than is observed. In light of these considerations, we conclude that HAWC's highest energy sources should be interpreted as TeV halos or pulsar wind nebulae, which produce their emission through inverse Compton scattering, and are powered by the rotational kinetic energy of their host pulsar.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

PHYSICAL PROPERTIES OF NEAR-EARTH ASTEROID 2011 MD

We report on observations of near-Earth asteroid 2011 MD with the Spitzer Space Telescope. We have spent 19.9 hr of observing time with channel 2 (4.5 μm) of the Infrared Array Camera and detected the target within the 2σ positional uncertainty ellipse. Using an asteroid thermophysical model and a model of nongravitational forces acting upon the object, we constrain the physical properties of 2011 MD, based on the measured flux density and available astrometry data. We estimate 2011 MD to be (6{sub −2}{sup +4}) m in diameter with a geometric albedo of 0.3{sub −0.2}{sup +0.4} (uncertainties are 1σ). We find the asteroid's most probable bulk density to be (1.1{sub −0.5}{sup +0.7}) g cm{sup –3}, which implies a total mass of (50-350) t and a macroporosity of ≥65%, assuming a material bulk density typical of non-primitive meteorite materials. A high degree of macroporosity suggests that 2011 MD is a rubble-pile asteroid, the rotation of which is more likely to be retrograde than prograde.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Redshift drift cosmography with ELT and SKAO measurements

ABSTRACT Mapping the expansion history of the universe is a compelling task of physical cosmology, especially in the context of the observational evidence for the recent acceleration of the universe, which demonstrates that canonical theories of cosmology and particle physics are incomplete and that there is new physics still to be discovered. Cosmography is a phenomenological approach to cosmology, where (with some caveats) physical quantities are expanded as a Taylor series in the cosmological redshift z, or analogous parameters such as the rescaled redshift y = z/(1 + z) or the logarithmic redshift x = ln (1 + z). Moreover, the redshift drift of objects following cosmological expansion provides a model-independent observable, detectable by facilities currently under construction, viz. the Extremely Large Telescope and the Square Kilometre Array Observatory (at least in its full configuration). Here, we use simulated redshift drift measurements from the two facilities to carry out an assessment of the cosmological impact and model discriminating power of redshift drift cosmography. We find that the combination of measurements from the two facilities can provide a stringent test of the Λ cold dark matter paradigm, and that overall the logarithmic-based expansions of the spectroscopic velocity drift are the most reliable ones, performing better than analogous expansions in the redshift or the rescaled redshift: the former nominally gives the smaller error bars for the cosmographic coefficients but is vulnerable to biases in the higher order terms (in other words, it is only reliable at low redshifts), while the latter always performs poorly.

Rocha, B. A. R.↗
DOE OSTI2022

A spectrophotometric analysis of cool white dwarfs in the Gaia and pan-STARRS footprint

We present a spectrophotometric analysis of 2880 cool white dwarfs within 100 pc of the Sun and cooler than T eff ∼ 10 000 K, with grizy Pan-STARRS photometry and Gaia trigonometric parallaxes available. We also supplement our data sets with near-infrared JHK photometry, when available, which is shown to be essential for interpreting the coolest white dwarfs in our sample. We perform a detailed analysis of each individual object using state-of-the-art model atmospheres appropriate for each spectral type, including DA, DC, DQ, DZ, He-rich DA, and the so-called IR-faint white dwarfs. We discuss the temperature and mass distributions of each subsample, as well as revisit the spectral evolution of cool white dwarfs. We find little evidence in our sample for the transformation of a significant fraction of DA stars into He-atmosphere white dwarfs through the process of convective mixing between T eff = 10 000 and ∼6500 K, although the situation changes drastically in the range T eff = 6500–5500 K where the fraction of He-atmosphere white dwarfs reaches ∼45 per cent. However, we also provide strong evidence that at even cooler temperatures (T eff ≲ 5200 K), most DC white dwarfs have H atmospheres. We discuss a possible mechanism to account for this sudden transformation from He- to H-atmosphere white dwarfs involving the onset of crystallization and the occurrence of magnetism. Finally, we also argue that DQ, DZ, and DC white dwarfs may form a more homogeneous population than previously believed.

79 ASTRONOMY AND ASTROPHYSICS↗